code: def test_mlp(self, device, dtype):
      d_input = 63  # Input dimension after encoding
      num_hidden = 256
      mlp = MLP(
          d_input, num_units=2, num_unit_layers=4, num_hidden=num_hidden
      )
      mlp.to(device=device, dtype=dtype)
  
      num_rays = 15
      num_ray_points = 11
      x = torch.rand(
          num_rays, num_ray_points, d_input, device=device, dtype=dtype
      )
      xout = mlp(x)
      assert xout.shape == (num_rays, num_ray_points, num_hidden)
  
file_path: kornia/test/nerf/test_nerf_model.py
imports: import pytest
  import torch
  from kornia.geometry.camera import PinholeCamera
  from kornia.nerf.nerf_model import MLP, NerfModel, NerfModelRenderer
label_desc: Use image node_id 1 for calling the TestNerfModel obj's underlying member method code with example usage: obj.test_mlp(device, dtype) without return types